Position-aware applications such as navigation tools for humans and robots, interactive virtual games, resource discovery, asset tracking, position-aware sensor networking etc. require precise positioning. These indoor applications require better accuracy than what current outdoor positioning systems provide. This book presents some new algorithms for position estimation in RFID, WSN and VLC technologies. We design some RSS positioning algorithms for RFID and WSN using flexible models. Using the time difference of arrival (TDOA) and RSS measurement functionally of a commercially available RFID system, a position finding algorithm is presented where the position is estimated in two steps. As a practical application of this system, an automatic parking management system is described in this book. For positioning in WSN, RSS based algorithms with flexible model of multi-layer parceptron and generalized regression neural networks are proposed. This book also demonstrates a robust, high accuracy positioning algorithm using VLC and image sensors for precisely locating movable objects, like autonomous robot inside the building.

Mohammad Shaifur Rahman, PhD: Completed both Bachelor and Master degree in Electrical and Electronic Engineering at Khulna University of Engineering and Technology (KUET), Bangladesh, and PhD in Electronics Engineering at Kookmin University, Republic of Korea. Now Associate Professor in the Department of Electrical and Electronic Engineering, KUET.